We present a new family of snakes that satisfy the property of multiresolution by exploiting subdivision schemes. We show in a generic way how to construct such snakes based on an admissible subdivision mask. We derive the necessary energy formulations and provide the formulas for their efficient computation. Depending on the choice of the mask, such models have the ability to reproduce trigonometric or polynomial curves. They can also be designed to be interpolating, a property that is useful in user-interactive applications. We provide explicit examples of subdivision snakes and illustrate their use for the segmentation of bioimages. We show that they are robust in the presence of noise and provide a multiresolution algorithm to enlarge their basin of attraction, which decreases their dependence on initialization compared to singleresolution snakes. We show the advantages of the proposed model in terms of computation and segmentation of structures with different sizes.
A. Badoual, D. Schmitter, V. Uhlmann, M. Unser, "Multiresolution Subdivision Snakes, " IEEE Transactions on Image Processing, 2017.
Open Source Plugin: AC_SubdivisionSnakes
The method is implemented as a plugin for the Icy bioimaging platform.
Condition of useThe software is freely available for research purposes. However, it should not be redistributed without the consent of the authors. We expect the user to include a citation of this publication whenever presenting or publishing results that are based on the Icy plugin AC_SubdivisionSnakes.